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<div class="title">TensorBroadcasting.h</div>  </div>
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<div class="contents">
<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">// This file is part of Eigen, a lightweight C++ template library</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// for linear algebra.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">// Copyright (C) 2014 Benoit Steiner &lt;benoit.steiner.goog@gmail.com&gt;</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment">// This Source Code Form is subject to the terms of the Mozilla</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment">// Public License v. 2.0. If a copy of the MPL was not distributed</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment">// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160; </div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#ifndef EIGEN_CXX11_TENSOR_TENSOR_BROADCASTING_H</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#define EIGEN_CXX11_TENSOR_TENSOR_BROADCASTING_H</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160; </div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="preprocessor">#include &quot;./InternalHeaderCheck.h&quot;</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160; </div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespaceEigen.html">Eigen</a> {</div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160; </div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="keyword">namespace </span>internal {</div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Broadcast, <span class="keyword">typename</span> XprType&gt;</div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="keyword">struct </span>traits&lt;TensorBroadcastingOp&lt;Broadcast, XprType&gt; &gt; : <span class="keyword">public</span> traits&lt;XprType&gt;</div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;{</div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprType::Scalar Scalar;</div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;  <span class="keyword">typedef</span> traits&lt;XprType&gt; XprTraits;</div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprTraits::StorageKind StorageKind;</div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprTraits::Index <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>;</div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprType::Nested Nested;</div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;  <span class="keyword">typedef</span> std::remove_reference_t&lt;Nested&gt; Nested_;</div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> NumDimensions = XprTraits::NumDimensions;</div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> Layout = XprTraits::Layout;</div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprTraits::PointerType PointerType;</div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;};</div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160; </div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Broadcast, <span class="keyword">typename</span> XprType&gt;</div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="keyword">struct </span>eval&lt;TensorBroadcastingOp&lt;Broadcast, XprType&gt;, <a class="code" href="namespaceEigen.html">Eigen</a>::Dense&gt;</div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;{</div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">const</span> TensorBroadcastingOp&lt;Broadcast, XprType&gt; EIGEN_DEVICE_REF type;</div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;};</div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160; </div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Broadcast, <span class="keyword">typename</span> XprType&gt;</div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="keyword">struct </span>nested&lt;TensorBroadcastingOp&lt;Broadcast, XprType&gt;, 1, typename eval&lt;TensorBroadcastingOp&lt;Broadcast, XprType&gt; &gt;::type&gt;</div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;{</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;  <span class="keyword">typedef</span> TensorBroadcastingOp&lt;Broadcast, XprType&gt; type;</div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;};</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160; </div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Dims&gt;</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;<span class="keyword">struct </span>is_input_scalar {</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;  <span class="keyword">static</span> <span class="keyword">const</span> <span class="keywordtype">bool</span> value = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;};</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;<span class="keyword">template</span> &lt;&gt;</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;<span class="keyword">struct </span>is_input_scalar&lt;Sizes&lt;&gt; &gt; {</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;  <span class="keyword">static</span> <span class="keyword">const</span> <span class="keywordtype">bool</span> value = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;};</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;<span class="preprocessor">#ifndef EIGEN_EMULATE_CXX11_META_H</span></div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> std::ptrdiff_t... Indices&gt;</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;<span class="keyword">struct </span>is_input_scalar&lt;Sizes&lt;Indices...&gt; &gt; {</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;  <span class="keyword">static</span> <span class="keyword">const</span> <span class="keywordtype">bool</span> value = (Sizes&lt;Indices...&gt;::total_size == 1);</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;};</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160; </div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;}  <span class="comment">// end namespace internal</span></div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160; </div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160; </div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160; </div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Broadcast, <span class="keyword">typename</span> XprType&gt;</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;<span class="keyword">class </span>TensorBroadcastingOp : <span class="keyword">public</span> TensorBase&lt;TensorBroadcastingOp&lt;Broadcast, XprType&gt;, ReadOnlyAccessors&gt;</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;{</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;  <span class="keyword">public</span>:</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Eigen::internal::traits&lt;TensorBroadcastingOp&gt;::Scalar Scalar;</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="codeRef" href="../structEigen_1_1NumTraits.html">Eigen::NumTraits&lt;Scalar&gt;::Real</a> RealScalar;</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprType::CoeffReturnType CoeffReturnType;</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Eigen::internal::nested&lt;TensorBroadcastingOp&gt;::type Nested;</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Eigen::internal::traits&lt;TensorBroadcastingOp&gt;::StorageKind StorageKind;</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Eigen::internal::traits&lt;TensorBroadcastingOp&gt;::Index <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>;</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160; </div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorBroadcastingOp(<span class="keyword">const</span> XprType&amp; expr, <span class="keyword">const</span> Broadcast&amp; broadcast)</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;      : m_xpr(expr), m_broadcast(broadcast) {}</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160; </div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    EIGEN_DEVICE_FUNC</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    <span class="keyword">const</span> Broadcast&amp; broadcast()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_broadcast; }</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160; </div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    EIGEN_DEVICE_FUNC</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    <span class="keyword">const</span> internal::remove_all_t&lt;typename XprType::Nested&gt;&amp;</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    expression()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_xpr; }</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160; </div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;  <span class="keyword">protected</span>:</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <span class="keyword">typename</span> XprType::Nested m_xpr;</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    <span class="keyword">const</span> Broadcast m_broadcast;</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;};</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160; </div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160; </div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;<span class="comment">// Eval as rvalue</span></div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Broadcast, <span class="keyword">typename</span> ArgType, <span class="keyword">typename</span> Device&gt;</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;<span class="keyword">struct </span>TensorEvaluator&lt;const TensorBroadcastingOp&lt;Broadcast, ArgType&gt;, Device&gt;</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;{</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;  <span class="keyword">typedef</span> TensorBroadcastingOp&lt;Broadcast, ArgType&gt; XprType;</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprType::Index Index;</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> NumDims = internal::array_size&lt;typename TensorEvaluator&lt;ArgType, Device&gt;::Dimensions&gt;::value;</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;  <span class="keyword">typedef</span> DSizes&lt;Index, NumDims&gt; Dimensions;</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprType::Scalar Scalar;</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> TensorEvaluator&lt;ArgType, Device&gt;::Dimensions InputDimensions;</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprType::CoeffReturnType CoeffReturnType;</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> PacketType&lt;CoeffReturnType, Device&gt;::type PacketReturnType;</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> PacketSize = PacketType&lt;CoeffReturnType, Device&gt;::size;</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;  <span class="keyword">protected</span>: <span class="comment">//  all the non-static fields must have the same access control, otherwise the TensorEvaluator won&#39;t be standard layout;</span></div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;  <span class="keywordtype">bool</span> isCopy, nByOne, oneByN;</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;  <span class="keyword">public</span>:</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;  <span class="keyword">typedef</span> StorageMemory&lt;CoeffReturnType, Device&gt; Storage;</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Storage::Type EvaluatorPointerType;</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160; </div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    IsAligned         = TensorEvaluator&lt;ArgType, Device&gt;::IsAligned,</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    PacketAccess      = TensorEvaluator&lt;ArgType, Device&gt;::PacketAccess,</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    BlockAccess       = TensorEvaluator&lt;ArgType, Device&gt;::BlockAccess,</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    PreferBlockAccess = <span class="keyword">true</span>,</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    RawAccess         = <span class="keyword">false</span></div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;  };</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> Layout = TensorEvaluator&lt;ArgType, Device&gt;::Layout;</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160; </div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;  <span class="keyword">typedef</span> std::remove_const_t&lt;Scalar&gt; ScalarNoConst;</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160; </div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;  <span class="comment">// We do block based broadcasting using a trick with 2x tensor rank and 0</span></div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;  <span class="comment">// strides. See block method implementation for details.</span></div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;  <span class="keyword">typedef</span> DSizes&lt;Index, 2 * NumDims&gt; BroadcastDimensions;</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160; </div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;  <span class="comment">//===- Tensor block evaluation strategy (see TensorBlock.h) -------------===//</span></div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;  <span class="keyword">typedef</span> internal::TensorBlockDescriptor&lt;NumDims, Index&gt; TensorBlockDesc;</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;  <span class="keyword">typedef</span> internal::TensorBlockScratchAllocator&lt;Device&gt; TensorBlockScratch;</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160; </div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> TensorEvaluator&lt;const ArgType, Device&gt;::TensorBlock</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;      ArgTensorBlock;</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160; </div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> internal::TensorMaterializedBlock&lt;ScalarNoConst, NumDims,</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;                                                     Layout, <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>&gt;</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;      TensorBlock;</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;  <span class="comment">//===--------------------------------------------------------------------===//</span></div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160; </div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;  EIGEN_STRONG_INLINE TensorEvaluator(<span class="keyword">const</span> XprType&amp; op, <span class="keyword">const</span> Device&amp; device)</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;      : isCopy(false), nByOne(false), oneByN(false),</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;        m_device(device), m_broadcast(op.broadcast()), m_impl(op.expression(), device)</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;  {</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160; </div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="comment">// The broadcasting op doesn&#39;t change the rank of the tensor. One can&#39;t broadcast a scalar</span></div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    <span class="comment">// and store the result in a scalar. Instead one should reshape the scalar into a N-D</span></div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;    <span class="comment">// tensor with N &gt;= 1 of 1 element first and then broadcast.</span></div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    EIGEN_STATIC_ASSERT((NumDims &gt; 0), YOU_MADE_A_PROGRAMMING_MISTAKE);</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    <span class="keyword">const</span> InputDimensions&amp; input_dims = m_impl.dimensions();</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    isCopy = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; NumDims; ++i) {</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;      eigen_assert(input_dims[i] &gt; 0);</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;      m_dimensions[i] = input_dims[i] * m_broadcast[i];</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;      <span class="keywordflow">if</span> (m_broadcast[i] != 1) {</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;        isCopy = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;      }</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;    }</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160; </div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    <span class="keywordflow">if</span> (<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(Layout) == <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(<a class="codeRef" href="../group__enums.html#ggaacded1a18ae58b0f554751f6cdf9eb13a0103672ae41005ab03b4176c765afd62">ColMajor</a>)) {</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;      m_inputStrides[0] = 1;</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;      m_outputStrides[0] = 1;</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 1; i &lt; NumDims; ++i) {</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;        m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;        m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;      }</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;      m_inputStrides[NumDims-1] = 1;</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;      m_outputStrides[NumDims-1] = 1;</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = NumDims-2; i &gt;= 0; --i) {</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;        m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1];</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;        m_outputStrides[i] = m_outputStrides[i+1] * m_dimensions[i+1];</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;      }</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;    }</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160; </div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    <span class="keywordflow">if</span> (input_dims[0] == 1) {</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;      oneByN = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 1; i &lt; NumDims; ++i) {</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;        <span class="keywordflow">if</span> (m_broadcast[i] != 1) {</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;          oneByN = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;          <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;        }</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;      }</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (input_dims[NumDims-1] == 1) {</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;      nByOne = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; NumDims-1; ++i) {</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;        <span class="keywordflow">if</span> (m_broadcast[i] != 1) {</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;          nByOne = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;          <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;        }</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;      }</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;    }</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160; </div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;    <span class="comment">// Handle special format like NCHW, its input shape is &#39;[1, N..., 1]&#39; and</span></div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;    <span class="comment">// broadcast shape is &#39;[N, 1..., N]&#39;</span></div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;    <span class="keywordflow">if</span> (!oneByN &amp;&amp; !nByOne) {</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;      <span class="keywordflow">if</span> (input_dims[0] == 1 &amp;&amp; input_dims[NumDims-1] == 1 &amp;&amp; NumDims &gt; 2) {</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;        nByOne = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;        oneByN = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 1; i &lt; NumDims-1; ++i) {</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;          <span class="keywordflow">if</span> (m_broadcast[i] != 1) {</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;            nByOne = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;            oneByN = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;            <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;          }</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;        }</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;      }</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;    }</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;  }</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160; </div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">const</span> Dimensions&amp; dimensions()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_dimensions; }</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160; </div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;  EIGEN_STRONG_INLINE <span class="keywordtype">bool</span> evalSubExprsIfNeeded(EvaluatorPointerType) {</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;    m_impl.evalSubExprsIfNeeded(NULL);</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;  }</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160; </div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;<span class="preprocessor">#ifdef EIGEN_USE_THREADS</span></div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;  <span class="keyword">template</span> &lt;<span class="keyword">typename</span> EvalSubExprsCallback&gt;</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;  EIGEN_STRONG_INLINE <span class="keywordtype">void</span> evalSubExprsIfNeededAsync(</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;      EvaluatorPointerType, EvalSubExprsCallback done) {</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;    m_impl.evalSubExprsIfNeededAsync(<span class="keyword">nullptr</span>, [done](<span class="keywordtype">bool</span>) { done(<span class="keyword">true</span>); });</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;  }</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;<span class="preprocessor">#endif  </span><span class="comment">// EIGEN_USE_THREADS</span></div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160; </div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;  EIGEN_STRONG_INLINE <span class="keywordtype">void</span> cleanup() {</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;    m_impl.cleanup();</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;  }</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160; </div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE CoeffReturnType coeff(Index index)<span class="keyword"> const</span></div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;<span class="keyword">  </span>{</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;    <span class="keywordflow">if</span> (internal::is_input_scalar&lt;internal::remove_all_t&lt;InputDimensions&gt;&gt;::value) {</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;      <span class="keywordflow">return</span> m_impl.coeff(0);</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;    }</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160; </div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    <span class="keywordflow">if</span> (<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(Layout) == <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(<a class="codeRef" href="../group__enums.html#ggaacded1a18ae58b0f554751f6cdf9eb13a0103672ae41005ab03b4176c765afd62">ColMajor</a>)) {</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;      <span class="keywordflow">if</span> (isCopy) {</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;        <span class="keywordflow">return</span> m_impl.coeff(index);</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;        <span class="keywordflow">return</span> coeffColMajor(index);</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;      }</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;      <span class="keywordflow">if</span> (isCopy) {</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;        <span class="keywordflow">return</span> m_impl.coeff(index);</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;        <span class="keywordflow">return</span> coeffRowMajor(index);</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;      }</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;    }</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;  }</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160; </div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;  <span class="comment">// TODO: attempt to speed this up. The integer divisions and modulo are slow</span></div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> indexColMajor(Index index)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> inputIndex = 0;</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = NumDims - 1; i &gt; 0; --i) {</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;      <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> idx = index / m_outputStrides[i];</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;      <span class="keywordflow">if</span> (internal::index_statically_eq&lt;Broadcast&gt;(i, 1)) {</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;        eigen_assert(idx &lt; m_impl.dimensions()[i]);</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;        inputIndex += idx * m_inputStrides[i];</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;        <span class="keywordflow">if</span> (internal::index_statically_eq&lt;InputDimensions&gt;(i, 1)) {</div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;          eigen_assert(idx % m_impl.dimensions()[i] == 0);</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;          inputIndex += (idx % m_impl.dimensions()[i]) * m_inputStrides[i];</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;        }</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;      }</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;      index -= idx * m_outputStrides[i];</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    }</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;    <span class="keywordflow">if</span> (internal::index_statically_eq&lt;Broadcast&gt;(0, 1)) {</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;      eigen_assert(index &lt; m_impl.dimensions()[0]);</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;      inputIndex += index;</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;      <span class="keywordflow">if</span> (internal::index_statically_eq&lt;InputDimensions&gt;(0, 1)) {</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;        eigen_assert(index % m_impl.dimensions()[0] == 0);</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;        inputIndex += (index % m_impl.dimensions()[0]);</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;      }</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;    }</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;    <span class="keywordflow">return</span> inputIndex;</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;  }</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160; </div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeffColMajor(Index index)<span class="keyword"> const</span></div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;<span class="keyword">  </span>{</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;    <span class="keywordflow">return</span> m_impl.coeff(indexColMajor(index));</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;  }</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160; </div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> indexRowMajor(Index index)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> inputIndex = 0;</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; NumDims - 1; ++i) {</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;      <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> idx = index / m_outputStrides[i];</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;      <span class="keywordflow">if</span> (internal::index_statically_eq&lt;Broadcast&gt;(i, 1)) {</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;        eigen_assert(idx &lt; m_impl.dimensions()[i]);</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;        inputIndex += idx * m_inputStrides[i];</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;        <span class="keywordflow">if</span> (internal::index_statically_eq&lt;InputDimensions&gt;(i, 1)) {</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;          eigen_assert(idx % m_impl.dimensions()[i] == 0);</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;          inputIndex += (idx % m_impl.dimensions()[i]) * m_inputStrides[i];</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;        }</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;      }</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;      index -= idx * m_outputStrides[i];</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;    }</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;    <span class="keywordflow">if</span> (internal::index_statically_eq&lt;Broadcast&gt;(NumDims - 1, 1)) {</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;      eigen_assert(index &lt; m_impl.dimensions()[NumDims - 1]);</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;      inputIndex += index;</div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;      <span class="keywordflow">if</span> (internal::index_statically_eq&lt;InputDimensions&gt;(NumDims - 1, 1)) {</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;        eigen_assert(index % m_impl.dimensions()[NumDims - 1] == 0);</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;        inputIndex += (index % m_impl.dimensions()[NumDims - 1]);</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;      }</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;    }</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;    <span class="keywordflow">return</span> inputIndex;</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;  }</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160; </div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeffRowMajor(Index index)<span class="keyword"> const</span></div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;<span class="keyword">  </span>{</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;    <span class="keywordflow">return</span> m_impl.coeff(indexRowMajor(index));</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;  }</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160; </div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;  <span class="keyword">template</span>&lt;<span class="keywordtype">int</span> LoadMode&gt;</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketReturnType packet(Index index)<span class="keyword"> const</span></div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;<span class="keyword">  </span>{</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;    <span class="keywordflow">if</span> (internal::is_input_scalar&lt;internal::remove_all_t&lt;InputDimensions&gt;&gt;::value) {</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;      <span class="keywordflow">return</span> internal::pset1&lt;PacketReturnType&gt;(m_impl.coeff(0));</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;    }</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160; </div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;    <span class="keywordflow">if</span> (<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(Layout) == <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(<a class="codeRef" href="../group__enums.html#ggaacded1a18ae58b0f554751f6cdf9eb13a0103672ae41005ab03b4176c765afd62">ColMajor</a>)) {</div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;      <span class="keywordflow">if</span> (isCopy) {</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;<span class="preprocessor">        #ifdef EIGEN_GPU_COMPILE_PHASE</span></div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;        <span class="comment">// See PR 437: on NVIDIA P100 and K20m we observed a x3-4 speed up by enforcing</span></div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;        <span class="comment">// unaligned loads here. The reason is unclear though.</span></div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;        <span class="keywordflow">return</span> m_impl.template packet&lt;Unaligned&gt;(index);</div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;<span class="preprocessor">        #else</span></div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;        <span class="keywordflow">return</span> m_impl.template packet&lt;LoadMode&gt;(index);</div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;<span class="preprocessor">        #endif</span></div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;      } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (oneByN &amp;&amp; !nByOne) {</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;        <span class="keywordflow">return</span> packetNByOne&lt;LoadMode&gt;(index);</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;      } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (!oneByN &amp;&amp; nByOne) {</div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;        <span class="keywordflow">return</span> packetOneByN&lt;LoadMode&gt;(index);</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;      } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (oneByN &amp;&amp; nByOne) {</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;        <span class="keywordflow">return</span> packetOneByNByOne&lt;LoadMode&gt;(index);</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;        <span class="keywordflow">return</span> packetColMajor&lt;LoadMode&gt;(index);</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;      }</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;      <span class="keywordflow">if</span> (isCopy) {</div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;<span class="preprocessor">        #ifdef EIGEN_GPU_COMPILE_PHASE</span></div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;        <span class="comment">// See above.</span></div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;        <span class="keywordflow">return</span> m_impl.template packet&lt;Unaligned&gt;(index);</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;<span class="preprocessor">        #else</span></div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;        <span class="keywordflow">return</span> m_impl.template packet&lt;LoadMode&gt;(index);</div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;<span class="preprocessor">        #endif</span></div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;      } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (oneByN &amp;&amp; !nByOne) {</div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;        <span class="keywordflow">return</span> packetOneByN&lt;LoadMode&gt;(index);</div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;      } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (!oneByN &amp;&amp; nByOne) {</div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;        <span class="keywordflow">return</span> packetNByOne&lt;LoadMode&gt;(index);</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;      } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (oneByN &amp;&amp; nByOne) {</div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;        <span class="keywordflow">return</span> packetOneByNByOne&lt;LoadMode&gt;(index);</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;        <span class="keywordflow">return</span> packetRowMajor&lt;LoadMode&gt;(index);</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;      }</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;    }</div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;  }</div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160; </div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;  <span class="keyword">template</span>&lt;<span class="keywordtype">int</span> LoadMode&gt;</div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetOneByNByOne</div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;  (Index index)<span class="keyword"> const</span></div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;<span class="keyword">  </span>{</div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;    eigen_assert(index+PacketSize-1 &lt; dimensions().TotalSize());</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160; </div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;    EIGEN_ALIGN_MAX std::remove_const_t&lt;CoeffReturnType&gt; values[PacketSize];</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> startDim, endDim;</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> inputIndex, outputOffset, batchedIndex;</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160; </div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;    <span class="keywordflow">if</span> (<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(Layout) == <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(<a class="codeRef" href="../group__enums.html#ggaacded1a18ae58b0f554751f6cdf9eb13a0103672ae41005ab03b4176c765afd62">ColMajor</a>)) {</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;      startDim = NumDims - 1;</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;      endDim = 1;</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;      startDim = 0;</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;      endDim = NumDims - 2;</div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;    }</div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160; </div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;    batchedIndex = index % m_outputStrides[startDim];</div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;    inputIndex   = batchedIndex / m_outputStrides[endDim];</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;    outputOffset = batchedIndex % m_outputStrides[endDim];</div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160; </div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;    <span class="keywordflow">if</span> (outputOffset + PacketSize &lt;= m_outputStrides[endDim]) {</div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;      values[0] = m_impl.coeff(inputIndex);</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;      <span class="keywordflow">return</span> internal::pload1&lt;PacketReturnType&gt;(values);</div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0, cur = 0; i &lt; PacketSize; ++i, ++cur) {</div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;        <span class="keywordflow">if</span> (outputOffset + cur &lt; m_outputStrides[endDim]) {</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;          values[i] = m_impl.coeff(inputIndex);</div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;          ++inputIndex;</div>
<div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;          inputIndex = (inputIndex == m_inputStrides[startDim] ? 0 : inputIndex);</div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;          values[i] = m_impl.coeff(inputIndex);</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;          outputOffset = 0;</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;          cur = 0;</div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;        }</div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;      }</div>
<div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;      <span class="keywordflow">return</span> internal::pload&lt;PacketReturnType&gt;(values);</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;    }</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;  }</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160; </div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;  <span class="keyword">template</span>&lt;<span class="keywordtype">int</span> LoadMode&gt;</div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetOneByN(Index index)<span class="keyword"> const</span></div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;<span class="keyword">  </span>{</div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;    <span class="comment">// Consider the flattened tensor [v0, ..., vN],</span></div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;    <span class="comment">// Concatenates m_broadcast[dim] copies,</span></div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;    <span class="comment">//    [v0, ..., vN, v0, ..., vN, ... ]</span></div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;    <span class="comment">// with dim == NumDims - 1 for col-major, dim == 0 for row-major.</span></div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;    eigen_assert(index+PacketSize-1 &lt; dimensions().TotalSize());</div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160; </div>
<div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;    <span class="comment">// Size of flattened tensor.</span></div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> M = (<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(Layout) == <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(<a class="codeRef" href="../group__enums.html#ggaacded1a18ae58b0f554751f6cdf9eb13a0103672ae41005ab03b4176c765afd62">ColMajor</a>)) ?</div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;                      m_inputStrides[NumDims - 1] : m_inputStrides[0];</div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> inputIndex = index % M;</div>
<div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;    <span class="keywordflow">if</span> (inputIndex + PacketSize &lt;= M) {</div>
<div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;      <span class="keywordflow">return</span> m_impl.template packet&lt;Unaligned&gt;(inputIndex);</div>
<div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;      EIGEN_ALIGN_MAX std::remove_const_t&lt;CoeffReturnType&gt; values[PacketSize];</div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; PacketSize; ++i) {</div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;        <span class="keywordflow">if</span> (inputIndex &gt; M - 1) {</div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;          inputIndex = 0;</div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;        }</div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;        values[i] = m_impl.coeff(inputIndex++);</div>
<div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;      }</div>
<div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;      <span class="keywordflow">return</span> internal::pload&lt;PacketReturnType&gt;(values);</div>
<div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;    }</div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;  }</div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160; </div>
<div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;  <span class="keyword">template</span>&lt;<span class="keywordtype">int</span> LoadMode&gt;</div>
<div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetNByOne(Index index)<span class="keyword"> const</span></div>
<div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;<span class="keyword">  </span>{</div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160;    <span class="comment">// Consider the flattened tensor [v0, ..., vN],</span></div>
<div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;    <span class="comment">// Interleaves m_broadcast[dim] copies,</span></div>
<div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;    <span class="comment">//    [v0, v0, ..., v1, v1, ..., vN, vN, ... ]</span></div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;    <span class="comment">// with dim == 0 for col-major, dim == NumDims - 1 for row-major.</span></div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;    eigen_assert(index + PacketSize-1 &lt; dimensions().TotalSize());</div>
<div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160; </div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> M = (<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(Layout) == <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(<a class="codeRef" href="../group__enums.html#ggaacded1a18ae58b0f554751f6cdf9eb13a0103672ae41005ab03b4176c765afd62">ColMajor</a>)) ?</div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;                      m_broadcast[0] : m_broadcast[NumDims - 1];</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160; </div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> inputIndex   = index / M;</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> outputOffset = index % M;</div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;    <span class="keywordflow">if</span> (outputOffset + PacketSize &lt;= M) {</div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;      <span class="keywordflow">return</span> internal::pset1&lt;PacketReturnType&gt;(m_impl.coeff(inputIndex));</div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;      EIGEN_ALIGN_MAX std::remove_const_t&lt;CoeffReturnType&gt; values[PacketSize];</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; PacketSize; ++i) {</div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;        <span class="keywordflow">if</span> (outputOffset &lt; M) {</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;          values[i] = m_impl.coeff(inputIndex);</div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;          ++outputOffset;</div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;          values[i] = m_impl.coeff(++inputIndex);</div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;          outputOffset = 1;  <span class="comment">// Next offset.</span></div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;        }</div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;      }</div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;      <span class="keywordflow">return</span> internal::pload&lt;PacketReturnType&gt;(values);</div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;    }</div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;  }</div>
<div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160; </div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;  <span class="comment">// Ignore the LoadMode and always use unaligned loads since we can&#39;t guarantee</span></div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;  <span class="comment">// the alignment at compile time.</span></div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;  <span class="keyword">template</span>&lt;<span class="keywordtype">int</span> LoadMode&gt;</div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetColMajor(Index index)<span class="keyword"> const</span></div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;<span class="keyword">  </span>{</div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;    eigen_assert(index+PacketSize-1 &lt; dimensions().TotalSize());</div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160; </div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> originalIndex = index;</div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160; </div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> inputIndex = 0;</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = NumDims - 1; i &gt; 0; --i) {</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;      <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> idx = index / m_outputStrides[i];</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;      <span class="keywordflow">if</span> (internal::index_statically_eq&lt;Broadcast&gt;(i, 1)) {</div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;        eigen_assert(idx &lt; m_impl.dimensions()[i]);</div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;        inputIndex += idx * m_inputStrides[i];</div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;        <span class="keywordflow">if</span> (internal::index_statically_eq&lt;InputDimensions&gt;(i, 1)) {</div>
<div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;          eigen_assert(idx % m_impl.dimensions()[i] == 0);</div>
<div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;          inputIndex += (idx % m_impl.dimensions()[i]) * m_inputStrides[i];</div>
<div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;        }</div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;      }</div>
<div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;      index -= idx * m_outputStrides[i];</div>
<div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160;    }</div>
<div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> innermostLoc;</div>
<div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;    <span class="keywordflow">if</span> (internal::index_statically_eq&lt;Broadcast&gt;(0, 1)) {</div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160;      eigen_assert(index &lt; m_impl.dimensions()[0]);</div>
<div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;      innermostLoc = index;</div>
<div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00501"></a><span class="lineno">  501</span>&#160;      <span class="keywordflow">if</span> (internal::index_statically_eq&lt;InputDimensions&gt;(0, 1)) {</div>
<div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;        eigen_assert(index % m_impl.dimensions()[0] == 0);</div>
<div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;        innermostLoc = 0;</div>
<div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;        innermostLoc = index % m_impl.dimensions()[0];</div>
<div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160;      }</div>
<div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;    }</div>
<div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;    inputIndex += innermostLoc;</div>
<div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160; </div>
<div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;    <span class="comment">// Todo: this could be extended to the second dimension if we&#39;re not</span></div>
<div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;    <span class="comment">// broadcasting alongside the first dimension, and so on.</span></div>
<div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;    <span class="keywordflow">if</span> (innermostLoc + PacketSize &lt;= m_impl.dimensions()[0]) {</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;      <span class="keywordflow">return</span> m_impl.template packet&lt;Unaligned&gt;(inputIndex);</div>
<div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;      EIGEN_ALIGN_MAX std::remove_const_t&lt;CoeffReturnType&gt; values[PacketSize];</div>
<div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;      values[0] = m_impl.coeff(inputIndex);</div>
<div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 1; i &lt; PacketSize; ++i) {</div>
<div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160;        <span class="keywordflow">if</span> (innermostLoc + i &lt; m_impl.dimensions()[0]) {</div>
<div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;          values[i] = m_impl.coeff(inputIndex+i);</div>
<div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160;          values[i] = coeffColMajor(originalIndex+i);</div>
<div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160;        }</div>
<div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;      }</div>
<div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160;      PacketReturnType rslt = internal::pload&lt;PacketReturnType&gt;(values);</div>
<div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;      <span class="keywordflow">return</span> rslt;</div>
<div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;    }</div>
<div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160;  }</div>
<div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160; </div>
<div class="line"><a name="l00530"></a><span class="lineno">  530</span>&#160;  <span class="keyword">template</span>&lt;<span class="keywordtype">int</span> LoadMode&gt;</div>
<div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetRowMajor(Index index)<span class="keyword"> const</span></div>
<div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;<span class="keyword">  </span>{</div>
<div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;    eigen_assert(index+PacketSize-1 &lt; dimensions().TotalSize());</div>
<div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160; </div>
<div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> originalIndex = index;</div>
<div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160; </div>
<div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> inputIndex = 0;</div>
<div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; NumDims - 1; ++i) {</div>
<div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;      <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> idx = index / m_outputStrides[i];</div>
<div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;      <span class="keywordflow">if</span> (internal::index_statically_eq&lt;Broadcast&gt;(i, 1)) {</div>
<div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160;        eigen_assert(idx &lt; m_impl.dimensions()[i]);</div>
<div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;        inputIndex += idx * m_inputStrides[i];</div>
<div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;        <span class="keywordflow">if</span> (internal::index_statically_eq&lt;InputDimensions&gt;(i, 1)) {</div>
<div class="line"><a name="l00546"></a><span class="lineno">  546</span>&#160;          eigen_assert(idx % m_impl.dimensions()[i] == 0);</div>
<div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160;          inputIndex += (idx % m_impl.dimensions()[i]) * m_inputStrides[i];</div>
<div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160;        }</div>
<div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;      }</div>
<div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;      index -= idx * m_outputStrides[i];</div>
<div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;    }</div>
<div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> innermostLoc;</div>
<div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;    <span class="keywordflow">if</span> (internal::index_statically_eq&lt;Broadcast&gt;(NumDims-1, 1)) {</div>
<div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;      eigen_assert(index &lt; m_impl.dimensions()[NumDims-1]);</div>
<div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;      innermostLoc = index;</div>
<div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;      <span class="keywordflow">if</span> (internal::index_statically_eq&lt;InputDimensions&gt;(NumDims-1, 1)) {</div>
<div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;        eigen_assert(index % m_impl.dimensions()[NumDims-1] == 0);</div>
<div class="line"><a name="l00560"></a><span class="lineno">  560</span>&#160;        innermostLoc = 0;</div>
<div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;        innermostLoc = index % m_impl.dimensions()[NumDims-1];</div>
<div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;      }</div>
<div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160;    }</div>
<div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;    inputIndex += innermostLoc;</div>
<div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160; </div>
<div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;    <span class="comment">// Todo: this could be extended to the second dimension if we&#39;re not</span></div>
<div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;    <span class="comment">// broadcasting alongside the first dimension, and so on.</span></div>
<div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160;    <span class="keywordflow">if</span> (innermostLoc + PacketSize &lt;= m_impl.dimensions()[NumDims-1]) {</div>
<div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160;      <span class="keywordflow">return</span> m_impl.template packet&lt;Unaligned&gt;(inputIndex);</div>
<div class="line"><a name="l00571"></a><span class="lineno">  571</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;      EIGEN_ALIGN_MAX std::remove_const_t&lt;CoeffReturnType&gt; values[PacketSize];</div>
<div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;      values[0] = m_impl.coeff(inputIndex);</div>
<div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 1; i &lt; PacketSize; ++i) {</div>
<div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;        <span class="keywordflow">if</span> (innermostLoc + i &lt; m_impl.dimensions()[NumDims-1]) {</div>
<div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;          values[i] = m_impl.coeff(inputIndex+i);</div>
<div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;          values[i] = coeffRowMajor(originalIndex+i);</div>
<div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;        }</div>
<div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;      }</div>
<div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;      PacketReturnType rslt = internal::pload&lt;PacketReturnType&gt;(values);</div>
<div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;      <span class="keywordflow">return</span> rslt;</div>
<div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;    }</div>
<div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;  }</div>
<div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160; </div>
<div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost</div>
<div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160;  costPerCoeff(<span class="keywordtype">bool</span> vectorized)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;    <span class="keywordtype">double</span> compute_cost = TensorOpCost::AddCost&lt;Index&gt;();</div>
<div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160;    <span class="keywordflow">if</span> (!isCopy &amp;&amp; NumDims &gt; 0) {</div>
<div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = NumDims - 1; i &gt; 0; --i) {</div>
<div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;        compute_cost += TensorOpCost::DivCost&lt;Index&gt;();</div>
<div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;        <span class="keywordflow">if</span> (internal::index_statically_eq&lt;Broadcast&gt;(i, 1)) {</div>
<div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;          compute_cost +=</div>
<div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160;              TensorOpCost::MulCost&lt;Index&gt;() + TensorOpCost::AddCost&lt;Index&gt;();</div>
<div class="line"><a name="l00597"></a><span class="lineno">  597</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;          <span class="keywordflow">if</span> (!internal::index_statically_eq&lt;InputDimensions&gt;(i, 1)) {</div>
<div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160;            compute_cost += TensorOpCost::MulCost&lt;Index&gt;() +</div>
<div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;                            TensorOpCost::ModCost&lt;Index&gt;() +</div>
<div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;                            TensorOpCost::AddCost&lt;Index&gt;();</div>
<div class="line"><a name="l00602"></a><span class="lineno">  602</span>&#160;          }</div>
<div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;        }</div>
<div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;        compute_cost +=</div>
<div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160;            TensorOpCost::MulCost&lt;Index&gt;() + TensorOpCost::AddCost&lt;Index&gt;();</div>
<div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;      }</div>
<div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;    }</div>
<div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160;    <span class="keywordflow">return</span> m_impl.costPerCoeff(vectorized) +</div>
<div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;           TensorOpCost(0, 0, compute_cost, vectorized, PacketSize);</div>
<div class="line"><a name="l00610"></a><span class="lineno">  610</span>&#160;  }</div>
<div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160; </div>
<div class="line"><a name="l00612"></a><span class="lineno">  612</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00613"></a><span class="lineno">  613</span>&#160;  internal::TensorBlockResourceRequirements getResourceRequirements()<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;    <span class="comment">// TODO(wuke): Targeting L1 size is 30% faster than targeting L{-1} on large</span></div>
<div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;    <span class="comment">// tensors. But this might need further tuning.</span></div>
<div class="line"><a name="l00616"></a><span class="lineno">  616</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> target_size = m_device.firstLevelCacheSize();</div>
<div class="line"><a name="l00617"></a><span class="lineno">  617</span>&#160;    <span class="keywordflow">return</span> internal::TensorBlockResourceRequirements::merge(</div>
<div class="line"><a name="l00618"></a><span class="lineno">  618</span>&#160;        m_impl.getResourceRequirements(),</div>
<div class="line"><a name="l00619"></a><span class="lineno">  619</span>&#160;        internal::TensorBlockResourceRequirements::skewed&lt;Scalar&gt;(target_size));</div>
<div class="line"><a name="l00620"></a><span class="lineno">  620</span>&#160;  }</div>
<div class="line"><a name="l00621"></a><span class="lineno">  621</span>&#160; </div>
<div class="line"><a name="l00622"></a><span class="lineno">  622</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorBlock</div>
<div class="line"><a name="l00623"></a><span class="lineno">  623</span>&#160;  block(TensorBlockDesc&amp; desc, TensorBlockScratch&amp; scratch,</div>
<div class="line"><a name="l00624"></a><span class="lineno">  624</span>&#160;          <span class="keywordtype">bool</span> <span class="comment">/*root_of_expr_ast*/</span> = <span class="keyword">false</span>)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00625"></a><span class="lineno">  625</span>&#160;    BlockBroadcastingParams params = blockBroadcastingParams(desc);</div>
<div class="line"><a name="l00626"></a><span class="lineno">  626</span>&#160; </div>
<div class="line"><a name="l00627"></a><span class="lineno">  627</span>&#160;    <span class="keywordflow">if</span> (params.inner_dim_size == 0 || params.bcast_dim_size == 0) {</div>
<div class="line"><a name="l00628"></a><span class="lineno">  628</span>&#160;      <span class="keywordflow">return</span> emptyBlock();</div>
<div class="line"><a name="l00629"></a><span class="lineno">  629</span>&#160;    }</div>
<div class="line"><a name="l00630"></a><span class="lineno">  630</span>&#160; </div>
<div class="line"><a name="l00631"></a><span class="lineno">  631</span>&#160;    <span class="comment">// Prepare storage for the materialized broadcasting result.</span></div>
<div class="line"><a name="l00632"></a><span class="lineno">  632</span>&#160;    <span class="keyword">const</span> <span class="keyword">typename</span> TensorBlock::Storage block_storage =</div>
<div class="line"><a name="l00633"></a><span class="lineno">  633</span>&#160;        TensorBlock::prepareStorage(desc, scratch);</div>
<div class="line"><a name="l00634"></a><span class="lineno">  634</span>&#160;    ScalarNoConst* materialized_output = block_storage.data();</div>
<div class="line"><a name="l00635"></a><span class="lineno">  635</span>&#160; </div>
<div class="line"><a name="l00636"></a><span class="lineno">  636</span>&#160;    <span class="comment">// We potentially will need to materialize input blocks.</span></div>
<div class="line"><a name="l00637"></a><span class="lineno">  637</span>&#160;    <span class="keywordtype">size_t</span> materialized_input_size = 0;</div>
<div class="line"><a name="l00638"></a><span class="lineno">  638</span>&#160;    ScalarNoConst* materialized_input = NULL;</div>
<div class="line"><a name="l00639"></a><span class="lineno">  639</span>&#160; </div>
<div class="line"><a name="l00640"></a><span class="lineno">  640</span>&#160;    <span class="comment">// Initialize block broadcating iterator state for outer dimensions (outer</span></div>
<div class="line"><a name="l00641"></a><span class="lineno">  641</span>&#160;    <span class="comment">// with regard to bcast dimension). Dimension in this array are always in</span></div>
<div class="line"><a name="l00642"></a><span class="lineno">  642</span>&#160;    <span class="comment">// inner_most -&gt; outer_most order (col major layout).</span></div>
<div class="line"><a name="l00643"></a><span class="lineno">  643</span>&#160;    array&lt;BlockBroadcastingIteratorState, NumDims&gt; it;</div>
<div class="line"><a name="l00644"></a><span class="lineno">  644</span>&#160;    <span class="keywordtype">int</span> idx = 0;</div>
<div class="line"><a name="l00645"></a><span class="lineno">  645</span>&#160; </div>
<div class="line"><a name="l00646"></a><span class="lineno">  646</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = params.inner_dim_count + 1; i &lt; NumDims; ++i) {</div>
<div class="line"><a name="l00647"></a><span class="lineno">  647</span>&#160;      <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> dim = IsColMajor ? i : NumDims - 1 - i;</div>
<div class="line"><a name="l00648"></a><span class="lineno">  648</span>&#160;      it[idx].size = params.output_dims[dim];</div>
<div class="line"><a name="l00649"></a><span class="lineno">  649</span>&#160;      it[idx].count = 0;</div>
<div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;      it[idx].output_stride = m_outputStrides[dim];</div>
<div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160;      it[idx].output_span = it[idx].output_stride * (it[idx].size - 1);</div>
<div class="line"><a name="l00652"></a><span class="lineno">  652</span>&#160;      idx++;</div>
<div class="line"><a name="l00653"></a><span class="lineno">  653</span>&#160;    }</div>
<div class="line"><a name="l00654"></a><span class="lineno">  654</span>&#160; </div>
<div class="line"><a name="l00655"></a><span class="lineno">  655</span>&#160;    <span class="comment">// Write output into the beginning of `materialized_output`.</span></div>
<div class="line"><a name="l00656"></a><span class="lineno">  656</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> output_offset = 0;</div>
<div class="line"><a name="l00657"></a><span class="lineno">  657</span>&#160; </div>
<div class="line"><a name="l00658"></a><span class="lineno">  658</span>&#160;    <span class="comment">// We will fill output block by broadcasting along the bcast dim, and</span></div>
<div class="line"><a name="l00659"></a><span class="lineno">  659</span>&#160;    <span class="comment">// iterating over outer dimension.</span></div>
<div class="line"><a name="l00660"></a><span class="lineno">  660</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> output_size = NumDims == 0 ? 1 : params.output_dims.TotalSize();</div>
<div class="line"><a name="l00661"></a><span class="lineno">  661</span>&#160; </div>
<div class="line"><a name="l00662"></a><span class="lineno">  662</span>&#160;    <span class="keywordflow">for</span> (Index num_output_coeffs = 0; num_output_coeffs &lt; output_size;) {</div>
<div class="line"><a name="l00663"></a><span class="lineno">  663</span>&#160;      ScalarNoConst* bcast_output = materialized_output + num_output_coeffs;</div>
<div class="line"><a name="l00664"></a><span class="lineno">  664</span>&#160;      <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> bcast_offset = desc.offset() + output_offset;</div>
<div class="line"><a name="l00665"></a><span class="lineno">  665</span>&#160; </div>
<div class="line"><a name="l00666"></a><span class="lineno">  666</span>&#160;      <span class="comment">// Broadcast along the bcast dimension.</span></div>
<div class="line"><a name="l00667"></a><span class="lineno">  667</span>&#160;      num_output_coeffs += BroadcastBlockAlongBcastDim(</div>
<div class="line"><a name="l00668"></a><span class="lineno">  668</span>&#160;          params, bcast_offset, scratch, bcast_output, &amp;materialized_input,</div>
<div class="line"><a name="l00669"></a><span class="lineno">  669</span>&#160;          &amp;materialized_input_size);</div>
<div class="line"><a name="l00670"></a><span class="lineno">  670</span>&#160; </div>
<div class="line"><a name="l00671"></a><span class="lineno">  671</span>&#160;      <span class="comment">// Switch to the next outer dimension.</span></div>
<div class="line"><a name="l00672"></a><span class="lineno">  672</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; idx; ++j) {</div>
<div class="line"><a name="l00673"></a><span class="lineno">  673</span>&#160;        <span class="keywordflow">if</span> (++it[j].count &lt; it[j].size) {</div>
<div class="line"><a name="l00674"></a><span class="lineno">  674</span>&#160;          output_offset += it[j].output_stride;</div>
<div class="line"><a name="l00675"></a><span class="lineno">  675</span>&#160;          <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00676"></a><span class="lineno">  676</span>&#160;        }</div>
<div class="line"><a name="l00677"></a><span class="lineno">  677</span>&#160;        it[j].count = 0;</div>
<div class="line"><a name="l00678"></a><span class="lineno">  678</span>&#160;        output_offset -= it[j].output_span;</div>
<div class="line"><a name="l00679"></a><span class="lineno">  679</span>&#160;      }</div>
<div class="line"><a name="l00680"></a><span class="lineno">  680</span>&#160;    }</div>
<div class="line"><a name="l00681"></a><span class="lineno">  681</span>&#160; </div>
<div class="line"><a name="l00682"></a><span class="lineno">  682</span>&#160;    <span class="keywordflow">return</span> block_storage.AsTensorMaterializedBlock();</div>
<div class="line"><a name="l00683"></a><span class="lineno">  683</span>&#160;  }</div>
<div class="line"><a name="l00684"></a><span class="lineno">  684</span>&#160; </div>
<div class="line"><a name="l00685"></a><span class="lineno">  685</span>&#160;  EIGEN_DEVICE_FUNC EvaluatorPointerType data()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> NULL; }</div>
<div class="line"><a name="l00686"></a><span class="lineno">  686</span>&#160; </div>
<div class="line"><a name="l00687"></a><span class="lineno">  687</span>&#160;  <span class="keyword">const</span> TensorEvaluator&lt;ArgType, Device&gt;&amp; impl()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_impl; }</div>
<div class="line"><a name="l00688"></a><span class="lineno">  688</span>&#160; </div>
<div class="line"><a name="l00689"></a><span class="lineno">  689</span>&#160;  Broadcast functor()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_broadcast; }</div>
<div class="line"><a name="l00690"></a><span class="lineno">  690</span>&#160;<span class="preprocessor">#ifdef EIGEN_USE_SYCL</span></div>
<div class="line"><a name="l00691"></a><span class="lineno">  691</span>&#160;  <span class="comment">// binding placeholder accessors to a command group handler for SYCL</span></div>
<div class="line"><a name="l00692"></a><span class="lineno">  692</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> bind(</div>
<div class="line"><a name="l00693"></a><span class="lineno">  693</span>&#160;      cl::sycl::handler&amp; cgh)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00694"></a><span class="lineno">  694</span>&#160;    m_impl.bind(cgh);</div>
<div class="line"><a name="l00695"></a><span class="lineno">  695</span>&#160;  }</div>
<div class="line"><a name="l00696"></a><span class="lineno">  696</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00697"></a><span class="lineno">  697</span>&#160; <span class="keyword">private</span>:</div>
<div class="line"><a name="l00698"></a><span class="lineno">  698</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">bool</span> IsColMajor =</div>
<div class="line"><a name="l00699"></a><span class="lineno">  699</span>&#160;      <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(Layout) == <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(<a class="codeRef" href="../group__enums.html#ggaacded1a18ae58b0f554751f6cdf9eb13a0103672ae41005ab03b4176c765afd62">ColMajor</a>);</div>
<div class="line"><a name="l00700"></a><span class="lineno">  700</span>&#160; </div>
<div class="line"><a name="l00701"></a><span class="lineno">  701</span>&#160;  <span class="comment">// We will build a general case block broadcasting on top of broadcasting</span></div>
<div class="line"><a name="l00702"></a><span class="lineno">  702</span>&#160;  <span class="comment">// primitive that will do broadcasting only for the inner dimension(s) along</span></div>
<div class="line"><a name="l00703"></a><span class="lineno">  703</span>&#160;  <span class="comment">// the first dimension smaller than the input size (it&#39;s called `bcast_dim`).</span></div>
<div class="line"><a name="l00704"></a><span class="lineno">  704</span>&#160;  <span class="comment">//</span></div>
<div class="line"><a name="l00705"></a><span class="lineno">  705</span>&#160;  <span class="comment">// Example:</span></div>
<div class="line"><a name="l00706"></a><span class="lineno">  706</span>&#160;  <span class="comment">//           dim:  0  1  2   (ColMajor)</span></div>
<div class="line"><a name="l00707"></a><span class="lineno">  707</span>&#160;  <span class="comment">//    input size: [9, 3, 6]</span></div>
<div class="line"><a name="l00708"></a><span class="lineno">  708</span>&#160;  <span class="comment">//    block size: [9, 2, 6]</span></div>
<div class="line"><a name="l00709"></a><span class="lineno">  709</span>&#160;  <span class="comment">//</span></div>
<div class="line"><a name="l00710"></a><span class="lineno">  710</span>&#160;  <span class="comment">// We will compute broadcasted block by iterating over the outer dimensions</span></div>
<div class="line"><a name="l00711"></a><span class="lineno">  711</span>&#160;  <span class="comment">// before `bcast_dim` (only dimension `2` in this example) and computing</span></div>
<div class="line"><a name="l00712"></a><span class="lineno">  712</span>&#160;  <span class="comment">// broadcasts along the `bcast_dim` (dimension `1` in this example).</span></div>
<div class="line"><a name="l00713"></a><span class="lineno">  713</span>&#160; </div>
<div class="line"><a name="l00714"></a><span class="lineno">  714</span>&#160;  <span class="comment">// BlockBroadcastingParams holds precomputed parameters for broadcasting a</span></div>
<div class="line"><a name="l00715"></a><span class="lineno">  715</span>&#160;  <span class="comment">// single block along the broadcasting dimension. Sizes and strides along the</span></div>
<div class="line"><a name="l00716"></a><span class="lineno">  716</span>&#160;  <span class="comment">// `bcast_dim` might be invalid, they will be adjusted later in</span></div>
<div class="line"><a name="l00717"></a><span class="lineno">  717</span>&#160;  <span class="comment">// `BroadcastBlockAlongBcastDim`.</span></div>
<div class="line"><a name="l00718"></a><span class="lineno">  718</span>&#160;  <span class="keyword">struct </span>BlockBroadcastingParams {</div>
<div class="line"><a name="l00719"></a><span class="lineno">  719</span>&#160;    Dimensions input_dims;      <span class="comment">// input expression dimensions</span></div>
<div class="line"><a name="l00720"></a><span class="lineno">  720</span>&#160;    Dimensions output_dims;     <span class="comment">// output block sizes</span></div>
<div class="line"><a name="l00721"></a><span class="lineno">  721</span>&#160;    Dimensions output_strides;  <span class="comment">// output block strides</span></div>
<div class="line"><a name="l00722"></a><span class="lineno">  722</span>&#160; </div>
<div class="line"><a name="l00723"></a><span class="lineno">  723</span>&#160;    <span class="keywordtype">int</span> inner_dim_count;   <span class="comment">// count inner dimensions matching in size</span></div>
<div class="line"><a name="l00724"></a><span class="lineno">  724</span>&#160;    <span class="keywordtype">int</span> bcast_dim;         <span class="comment">// broadcasting dimension index</span></div>
<div class="line"><a name="l00725"></a><span class="lineno">  725</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> bcast_dim_size;  <span class="comment">// broadcasting dimension size</span></div>
<div class="line"><a name="l00726"></a><span class="lineno">  726</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> inner_dim_size;  <span class="comment">// inner dimensions size</span></div>
<div class="line"><a name="l00727"></a><span class="lineno">  727</span>&#160; </div>
<div class="line"><a name="l00728"></a><span class="lineno">  728</span>&#160;    <span class="comment">// Block sizes and strides for the input block where all dimensions before</span></div>
<div class="line"><a name="l00729"></a><span class="lineno">  729</span>&#160;    <span class="comment">// `bcast_dim` are equal to `1`.</span></div>
<div class="line"><a name="l00730"></a><span class="lineno">  730</span>&#160;    Dimensions input_block_sizes;</div>
<div class="line"><a name="l00731"></a><span class="lineno">  731</span>&#160;    Dimensions input_block_strides;</div>
<div class="line"><a name="l00732"></a><span class="lineno">  732</span>&#160; </div>
<div class="line"><a name="l00733"></a><span class="lineno">  733</span>&#160;    <span class="comment">// Block sizes and strides for blocks with extra dimensions and strides `0`.</span></div>
<div class="line"><a name="l00734"></a><span class="lineno">  734</span>&#160;    BroadcastDimensions bcast_block_sizes;</div>
<div class="line"><a name="l00735"></a><span class="lineno">  735</span>&#160;    BroadcastDimensions bcast_block_strides;</div>
<div class="line"><a name="l00736"></a><span class="lineno">  736</span>&#160;    BroadcastDimensions bcast_input_strides;</div>
<div class="line"><a name="l00737"></a><span class="lineno">  737</span>&#160;  };</div>
<div class="line"><a name="l00738"></a><span class="lineno">  738</span>&#160; </div>
<div class="line"><a name="l00739"></a><span class="lineno">  739</span>&#160;  <span class="keyword">struct </span>BlockBroadcastingIteratorState {</div>
<div class="line"><a name="l00740"></a><span class="lineno">  740</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> size;</div>
<div class="line"><a name="l00741"></a><span class="lineno">  741</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> count;</div>
<div class="line"><a name="l00742"></a><span class="lineno">  742</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> output_stride;</div>
<div class="line"><a name="l00743"></a><span class="lineno">  743</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> output_span;</div>
<div class="line"><a name="l00744"></a><span class="lineno">  744</span>&#160;  };</div>
<div class="line"><a name="l00745"></a><span class="lineno">  745</span>&#160; </div>
<div class="line"><a name="l00746"></a><span class="lineno">  746</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE BlockBroadcastingParams</div>
<div class="line"><a name="l00747"></a><span class="lineno">  747</span>&#160;  blockBroadcastingParams(TensorBlockDesc&amp; desc)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00748"></a><span class="lineno">  748</span>&#160;    BlockBroadcastingParams params;</div>
<div class="line"><a name="l00749"></a><span class="lineno">  749</span>&#160; </div>
<div class="line"><a name="l00750"></a><span class="lineno">  750</span>&#160;    params.input_dims = Dimensions(m_impl.dimensions());</div>
<div class="line"><a name="l00751"></a><span class="lineno">  751</span>&#160; </div>
<div class="line"><a name="l00752"></a><span class="lineno">  752</span>&#160;    <span class="comment">// Output block sizes and strides.</span></div>
<div class="line"><a name="l00753"></a><span class="lineno">  753</span>&#160;    params.output_dims = desc.dimensions();</div>
<div class="line"><a name="l00754"></a><span class="lineno">  754</span>&#160;    params.output_strides = internal::strides&lt;Layout&gt;(params.output_dims);</div>
<div class="line"><a name="l00755"></a><span class="lineno">  755</span>&#160; </div>
<div class="line"><a name="l00756"></a><span class="lineno">  756</span>&#160;    <span class="comment">// Find the broadcasting dimension (first dimension with output size smaller</span></div>
<div class="line"><a name="l00757"></a><span class="lineno">  757</span>&#160;    <span class="comment">// that the input size).</span></div>
<div class="line"><a name="l00758"></a><span class="lineno">  758</span>&#160;    params.bcast_dim = 0;</div>
<div class="line"><a name="l00759"></a><span class="lineno">  759</span>&#160;    params.bcast_dim_size = 1;</div>
<div class="line"><a name="l00760"></a><span class="lineno">  760</span>&#160;    params.inner_dim_size = 1;</div>
<div class="line"><a name="l00761"></a><span class="lineno">  761</span>&#160; </div>
<div class="line"><a name="l00762"></a><span class="lineno">  762</span>&#160;    <span class="comment">// Count the number of inner dimensions that have the same size in the block</span></div>
<div class="line"><a name="l00763"></a><span class="lineno">  763</span>&#160;    <span class="comment">// and in the broadcast expression.</span></div>
<div class="line"><a name="l00764"></a><span class="lineno">  764</span>&#160;    params.inner_dim_count = 0;</div>
<div class="line"><a name="l00765"></a><span class="lineno">  765</span>&#160; </div>
<div class="line"><a name="l00766"></a><span class="lineno">  766</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; NumDims; ++i) {</div>
<div class="line"><a name="l00767"></a><span class="lineno">  767</span>&#160;      <span class="keyword">const</span> <span class="keywordtype">int</span> dim = IsColMajor ? i : NumDims - i - 1;</div>
<div class="line"><a name="l00768"></a><span class="lineno">  768</span>&#160; </div>
<div class="line"><a name="l00769"></a><span class="lineno">  769</span>&#160;      <span class="keywordflow">if</span> (params.output_dims[dim] == m_dimensions[dim]) {</div>
<div class="line"><a name="l00770"></a><span class="lineno">  770</span>&#160;        params.inner_dim_size *= params.output_dims[dim];</div>
<div class="line"><a name="l00771"></a><span class="lineno">  771</span>&#160;        ++params.inner_dim_count;</div>
<div class="line"><a name="l00772"></a><span class="lineno">  772</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00773"></a><span class="lineno">  773</span>&#160;      }</div>
<div class="line"><a name="l00774"></a><span class="lineno">  774</span>&#160; </div>
<div class="line"><a name="l00775"></a><span class="lineno">  775</span>&#160;      <span class="comment">// First non-matching dimension is the broadcasting dimension.</span></div>
<div class="line"><a name="l00776"></a><span class="lineno">  776</span>&#160;      eigen_assert(params.output_dims[dim] &lt; m_dimensions[dim]);</div>
<div class="line"><a name="l00777"></a><span class="lineno">  777</span>&#160;      params.bcast_dim = dim;</div>
<div class="line"><a name="l00778"></a><span class="lineno">  778</span>&#160;      params.bcast_dim_size = params.output_dims[dim];</div>
<div class="line"><a name="l00779"></a><span class="lineno">  779</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00780"></a><span class="lineno">  780</span>&#160;    }</div>
<div class="line"><a name="l00781"></a><span class="lineno">  781</span>&#160; </div>
<div class="line"><a name="l00782"></a><span class="lineno">  782</span>&#160;    <span class="comment">// Calculate the input block size for looking into the input.</span></div>
<div class="line"><a name="l00783"></a><span class="lineno">  783</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; params.inner_dim_count; ++i) {</div>
<div class="line"><a name="l00784"></a><span class="lineno">  784</span>&#160;      <span class="keyword">const</span> <span class="keywordtype">int</span> dim = IsColMajor ? i : NumDims - i - 1;</div>
<div class="line"><a name="l00785"></a><span class="lineno">  785</span>&#160;      params.input_block_sizes[dim] = params.input_dims[dim];</div>
<div class="line"><a name="l00786"></a><span class="lineno">  786</span>&#160;    }</div>
<div class="line"><a name="l00787"></a><span class="lineno">  787</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = params.inner_dim_count; i &lt; NumDims; ++i) {</div>
<div class="line"><a name="l00788"></a><span class="lineno">  788</span>&#160;      <span class="keyword">const</span> <span class="keywordtype">int</span> dim = IsColMajor ? i : NumDims - i - 1;</div>
<div class="line"><a name="l00789"></a><span class="lineno">  789</span>&#160;      params.input_block_sizes[dim] = 1;</div>
<div class="line"><a name="l00790"></a><span class="lineno">  790</span>&#160;    }</div>
<div class="line"><a name="l00791"></a><span class="lineno">  791</span>&#160;    params.input_block_strides =</div>
<div class="line"><a name="l00792"></a><span class="lineno">  792</span>&#160;        internal::strides&lt;Layout&gt;(params.input_block_sizes);</div>
<div class="line"><a name="l00793"></a><span class="lineno">  793</span>&#160; </div>
<div class="line"><a name="l00794"></a><span class="lineno">  794</span>&#160;    <span class="comment">// Broadcast with the 0-stride trick: Create 1 extra dim for each</span></div>
<div class="line"><a name="l00795"></a><span class="lineno">  795</span>&#160;    <span class="comment">// broadcast, set the input stride to 0.</span></div>
<div class="line"><a name="l00796"></a><span class="lineno">  796</span>&#160;    <span class="comment">//</span></div>
<div class="line"><a name="l00797"></a><span class="lineno">  797</span>&#160;    <span class="comment">// When ColMajor:</span></div>
<div class="line"><a name="l00798"></a><span class="lineno">  798</span>&#160;    <span class="comment">//</span></div>
<div class="line"><a name="l00799"></a><span class="lineno">  799</span>&#160;    <span class="comment">// - bcast_block_sizes:</span></div>
<div class="line"><a name="l00800"></a><span class="lineno">  800</span>&#160;    <span class="comment">//   [d_0, b_0, d_1, b_1, ...]</span></div>
<div class="line"><a name="l00801"></a><span class="lineno">  801</span>&#160;    <span class="comment">//</span></div>
<div class="line"><a name="l00802"></a><span class="lineno">  802</span>&#160;    <span class="comment">// - bcast_block_strides:</span></div>
<div class="line"><a name="l00803"></a><span class="lineno">  803</span>&#160;    <span class="comment">//   [output_block_strides[0], output_block_strides[0] * d_0,</span></div>
<div class="line"><a name="l00804"></a><span class="lineno">  804</span>&#160;    <span class="comment">//    output_block_strides[1], output_block_strides[1] * d_1,</span></div>
<div class="line"><a name="l00805"></a><span class="lineno">  805</span>&#160;    <span class="comment">//   ...]</span></div>
<div class="line"><a name="l00806"></a><span class="lineno">  806</span>&#160;    <span class="comment">//</span></div>
<div class="line"><a name="l00807"></a><span class="lineno">  807</span>&#160;    <span class="comment">// - bcast_input_strides:</span></div>
<div class="line"><a name="l00808"></a><span class="lineno">  808</span>&#160;    <span class="comment">//   [input_block_strides[0], 0,</span></div>
<div class="line"><a name="l00809"></a><span class="lineno">  809</span>&#160;    <span class="comment">//    input_block_strides[1], 0,</span></div>
<div class="line"><a name="l00810"></a><span class="lineno">  810</span>&#160;    <span class="comment">//   ...].</span></div>
<div class="line"><a name="l00811"></a><span class="lineno">  811</span>&#160;    <span class="comment">//</span></div>
<div class="line"><a name="l00812"></a><span class="lineno">  812</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; params.inner_dim_count; ++i) {</div>
<div class="line"><a name="l00813"></a><span class="lineno">  813</span>&#160;      <span class="keyword">const</span> <span class="keywordtype">int</span> dim = IsColMajor ? i : NumDims - i - 1;</div>
<div class="line"><a name="l00814"></a><span class="lineno">  814</span>&#160; </div>
<div class="line"><a name="l00815"></a><span class="lineno">  815</span>&#160;      <span class="keyword">const</span> <span class="keywordtype">int</span> copy_dim = IsColMajor ? 2 * i : 2 * NumDims - 2 * i - 1;</div>
<div class="line"><a name="l00816"></a><span class="lineno">  816</span>&#160;      <span class="keyword">const</span> <span class="keywordtype">int</span> broadcast_dim = IsColMajor ? copy_dim + 1 : copy_dim - 1;</div>
<div class="line"><a name="l00817"></a><span class="lineno">  817</span>&#160; </div>
<div class="line"><a name="l00818"></a><span class="lineno">  818</span>&#160;      params.bcast_block_sizes[copy_dim] = params.input_dims[dim];</div>
<div class="line"><a name="l00819"></a><span class="lineno">  819</span>&#160;      params.bcast_block_sizes[broadcast_dim] = m_broadcast[dim];</div>
<div class="line"><a name="l00820"></a><span class="lineno">  820</span>&#160;      params.bcast_block_strides[copy_dim] = params.output_strides[dim];</div>
<div class="line"><a name="l00821"></a><span class="lineno">  821</span>&#160;      params.bcast_block_strides[broadcast_dim] =</div>
<div class="line"><a name="l00822"></a><span class="lineno">  822</span>&#160;          params.output_strides[dim] * params.input_dims[dim];</div>
<div class="line"><a name="l00823"></a><span class="lineno">  823</span>&#160;      params.bcast_input_strides[copy_dim] = params.input_block_strides[dim];</div>
<div class="line"><a name="l00824"></a><span class="lineno">  824</span>&#160;      params.bcast_input_strides[broadcast_dim] = 0;</div>
<div class="line"><a name="l00825"></a><span class="lineno">  825</span>&#160;    }</div>
<div class="line"><a name="l00826"></a><span class="lineno">  826</span>&#160; </div>
<div class="line"><a name="l00827"></a><span class="lineno">  827</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 2 * params.inner_dim_count; i &lt; 2 * NumDims; ++i) {</div>
<div class="line"><a name="l00828"></a><span class="lineno">  828</span>&#160;      <span class="keyword">const</span> <span class="keywordtype">int</span> dim = IsColMajor ? i : 2 * NumDims - i - 1;</div>
<div class="line"><a name="l00829"></a><span class="lineno">  829</span>&#160;      params.bcast_block_sizes[dim] = 1;</div>
<div class="line"><a name="l00830"></a><span class="lineno">  830</span>&#160;      params.bcast_block_strides[dim] = 0;</div>
<div class="line"><a name="l00831"></a><span class="lineno">  831</span>&#160;      params.bcast_input_strides[dim] = 0;</div>
<div class="line"><a name="l00832"></a><span class="lineno">  832</span>&#160;    }</div>
<div class="line"><a name="l00833"></a><span class="lineno">  833</span>&#160; </div>
<div class="line"><a name="l00834"></a><span class="lineno">  834</span>&#160;    <span class="keywordflow">return</span> params;</div>
<div class="line"><a name="l00835"></a><span class="lineno">  835</span>&#160;  }</div>
<div class="line"><a name="l00836"></a><span class="lineno">  836</span>&#160; </div>
<div class="line"><a name="l00837"></a><span class="lineno">  837</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorBlock emptyBlock()<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00838"></a><span class="lineno">  838</span>&#160;    DSizes&lt;Index, NumDims&gt; dimensions;</div>
<div class="line"><a name="l00839"></a><span class="lineno">  839</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; NumDims; ++i) dimensions[i] = 0;</div>
<div class="line"><a name="l00840"></a><span class="lineno">  840</span>&#160;    <span class="keywordflow">return</span> TensorBlock(internal::TensorBlockKind::kView, NULL, dimensions);</div>
<div class="line"><a name="l00841"></a><span class="lineno">  841</span>&#160;  }</div>
<div class="line"><a name="l00842"></a><span class="lineno">  842</span>&#160; </div>
<div class="line"><a name="l00843"></a><span class="lineno">  843</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> BroadcastBlockAlongBcastDim(</div>
<div class="line"><a name="l00844"></a><span class="lineno">  844</span>&#160;      BlockBroadcastingParams params, Index bcast_offset,</div>
<div class="line"><a name="l00845"></a><span class="lineno">  845</span>&#160;      TensorBlockScratch&amp; scratch, ScalarNoConst* materialized_output,</div>
<div class="line"><a name="l00846"></a><span class="lineno">  846</span>&#160;      ScalarNoConst** materialized_input,</div>
<div class="line"><a name="l00847"></a><span class="lineno">  847</span>&#160;      <span class="keywordtype">size_t</span>* materialized_input_size)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00848"></a><span class="lineno">  848</span>&#160;    <span class="keywordflow">if</span> (params.bcast_dim_size == 1) {</div>
<div class="line"><a name="l00849"></a><span class="lineno">  849</span>&#160;      <span class="comment">// We just need one block read using the ready-set values above.</span></div>
<div class="line"><a name="l00850"></a><span class="lineno">  850</span>&#160;      <span class="keywordflow">return</span> BroadcastBlock(</div>
<div class="line"><a name="l00851"></a><span class="lineno">  851</span>&#160;          params.input_block_sizes, params.input_block_strides,</div>
<div class="line"><a name="l00852"></a><span class="lineno">  852</span>&#160;          params.bcast_block_sizes, params.bcast_block_strides,</div>
<div class="line"><a name="l00853"></a><span class="lineno">  853</span>&#160;          params.bcast_input_strides, bcast_offset, 0, scratch,</div>
<div class="line"><a name="l00854"></a><span class="lineno">  854</span>&#160;          materialized_output, materialized_input, materialized_input_size);</div>
<div class="line"><a name="l00855"></a><span class="lineno">  855</span>&#160; </div>
<div class="line"><a name="l00856"></a><span class="lineno">  856</span>&#160;    } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.input_dims[params.bcast_dim] == 1) {</div>
<div class="line"><a name="l00857"></a><span class="lineno">  857</span>&#160;      <span class="comment">// Broadcast bcast dimension (&lt; NumDims) by bcast_dim_size.</span></div>
<div class="line"><a name="l00858"></a><span class="lineno">  858</span>&#160;      <span class="keyword">const</span> <span class="keywordtype">int</span> broadcast_bcast_dim =</div>
<div class="line"><a name="l00859"></a><span class="lineno">  859</span>&#160;          IsColMajor ? 2 * params.inner_dim_count + 1</div>
<div class="line"><a name="l00860"></a><span class="lineno">  860</span>&#160;                     : 2 * NumDims - 2 * params.inner_dim_count - 2;</div>
<div class="line"><a name="l00861"></a><span class="lineno">  861</span>&#160; </div>
<div class="line"><a name="l00862"></a><span class="lineno">  862</span>&#160;      params.bcast_block_sizes[broadcast_bcast_dim] = params.bcast_dim_size;</div>
<div class="line"><a name="l00863"></a><span class="lineno">  863</span>&#160;      params.bcast_input_strides[broadcast_bcast_dim] = 0;</div>
<div class="line"><a name="l00864"></a><span class="lineno">  864</span>&#160;      params.bcast_block_strides[broadcast_bcast_dim] =</div>
<div class="line"><a name="l00865"></a><span class="lineno">  865</span>&#160;          params.output_strides[params.bcast_dim];</div>
<div class="line"><a name="l00866"></a><span class="lineno">  866</span>&#160; </div>
<div class="line"><a name="l00867"></a><span class="lineno">  867</span>&#160;      <span class="keywordflow">return</span> BroadcastBlock(</div>
<div class="line"><a name="l00868"></a><span class="lineno">  868</span>&#160;          params.input_block_sizes, params.input_block_strides,</div>
<div class="line"><a name="l00869"></a><span class="lineno">  869</span>&#160;          params.bcast_block_sizes, params.bcast_block_strides,</div>
<div class="line"><a name="l00870"></a><span class="lineno">  870</span>&#160;          params.bcast_input_strides, bcast_offset, 0, scratch,</div>
<div class="line"><a name="l00871"></a><span class="lineno">  871</span>&#160;          materialized_output, materialized_input, materialized_input_size);</div>
<div class="line"><a name="l00872"></a><span class="lineno">  872</span>&#160; </div>
<div class="line"><a name="l00873"></a><span class="lineno">  873</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00874"></a><span class="lineno">  874</span>&#160;      <span class="comment">// Keep track of the total number of the coefficients written to the</span></div>
<div class="line"><a name="l00875"></a><span class="lineno">  875</span>&#160;      <span class="comment">// output block.</span></div>
<div class="line"><a name="l00876"></a><span class="lineno">  876</span>&#160;      <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_output_coeffs = 0;</div>
<div class="line"><a name="l00877"></a><span class="lineno">  877</span>&#160; </div>
<div class="line"><a name="l00878"></a><span class="lineno">  878</span>&#160;      <span class="comment">// The general case. Let&#39;s denote the output block as</span></div>
<div class="line"><a name="l00879"></a><span class="lineno">  879</span>&#160;      <span class="comment">//</span></div>
<div class="line"><a name="l00880"></a><span class="lineno">  880</span>&#160;      <span class="comment">//   x[..., a:a+bcast_dim_size, :, ..., :]</span></div>
<div class="line"><a name="l00881"></a><span class="lineno">  881</span>&#160;      <span class="comment">//</span></div>
<div class="line"><a name="l00882"></a><span class="lineno">  882</span>&#160;      <span class="comment">// where a:a+bcast_dim_size is a slice on the bcast_dim dimension</span></div>
<div class="line"><a name="l00883"></a><span class="lineno">  883</span>&#160;      <span class="comment">// (&lt; NumDims). We need to split the a:a+bcast_dim_size into possibly 3</span></div>
<div class="line"><a name="l00884"></a><span class="lineno">  884</span>&#160;      <span class="comment">// sub-blocks:</span></div>
<div class="line"><a name="l00885"></a><span class="lineno">  885</span>&#160;      <span class="comment">//</span></div>
<div class="line"><a name="l00886"></a><span class="lineno">  886</span>&#160;      <span class="comment">// (1) a:b, where b is the smallest multiple of</span></div>
<div class="line"><a name="l00887"></a><span class="lineno">  887</span>&#160;      <span class="comment">//     input_dims[bcast_dim_start] in [a, a+bcast_dim_size].</span></div>
<div class="line"><a name="l00888"></a><span class="lineno">  888</span>&#160;      <span class="comment">//</span></div>
<div class="line"><a name="l00889"></a><span class="lineno">  889</span>&#160;      <span class="comment">// (2) b:c, where c is the largest multiple of input_dims[bcast_dim_start]</span></div>
<div class="line"><a name="l00890"></a><span class="lineno">  890</span>&#160;      <span class="comment">//     in [a, a+bcast_dim_size].</span></div>
<div class="line"><a name="l00891"></a><span class="lineno">  891</span>&#160;      <span class="comment">//</span></div>
<div class="line"><a name="l00892"></a><span class="lineno">  892</span>&#160;      <span class="comment">// (3) c:a+bcast_dim_size .</span></div>
<div class="line"><a name="l00893"></a><span class="lineno">  893</span>&#160;      <span class="comment">//</span></div>
<div class="line"><a name="l00894"></a><span class="lineno">  894</span>&#160;      <span class="comment">// Or, when b and c do not exist, we just need to process the whole block</span></div>
<div class="line"><a name="l00895"></a><span class="lineno">  895</span>&#160;      <span class="comment">// together.</span></div>
<div class="line"><a name="l00896"></a><span class="lineno">  896</span>&#160; </div>
<div class="line"><a name="l00897"></a><span class="lineno">  897</span>&#160;      <span class="comment">// Find a.</span></div>
<div class="line"><a name="l00898"></a><span class="lineno">  898</span>&#160;      <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> bcast_dim_left_index =</div>
<div class="line"><a name="l00899"></a><span class="lineno">  899</span>&#160;          bcast_offset / m_outputStrides[params.bcast_dim];</div>
<div class="line"><a name="l00900"></a><span class="lineno">  900</span>&#160; </div>
<div class="line"><a name="l00901"></a><span class="lineno">  901</span>&#160;      <span class="comment">// Find b and c.</span></div>
<div class="line"><a name="l00902"></a><span class="lineno">  902</span>&#160;      <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> input_bcast_dim_size = params.input_dims[params.bcast_dim];</div>
<div class="line"><a name="l00903"></a><span class="lineno">  903</span>&#160; </div>
<div class="line"><a name="l00904"></a><span class="lineno">  904</span>&#160;      <span class="comment">// First multiple after a. This is b when &lt;= bcast_dim_left_index +</span></div>
<div class="line"><a name="l00905"></a><span class="lineno">  905</span>&#160;      <span class="comment">// bcast_dim_size.</span></div>
<div class="line"><a name="l00906"></a><span class="lineno">  906</span>&#160;      <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> first_multiple =</div>
<div class="line"><a name="l00907"></a><span class="lineno">  907</span>&#160;          divup&lt;Index&gt;(bcast_dim_left_index, input_bcast_dim_size) *</div>
<div class="line"><a name="l00908"></a><span class="lineno">  908</span>&#160;          input_bcast_dim_size;</div>
<div class="line"><a name="l00909"></a><span class="lineno">  909</span>&#160; </div>
<div class="line"><a name="l00910"></a><span class="lineno">  910</span>&#160;      <span class="keywordflow">if</span> (first_multiple &lt;= bcast_dim_left_index + params.bcast_dim_size) {</div>
<div class="line"><a name="l00911"></a><span class="lineno">  911</span>&#160;        <span class="comment">// b exists, so does c. Find it.</span></div>
<div class="line"><a name="l00912"></a><span class="lineno">  912</span>&#160;        <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> last_multiple =</div>
<div class="line"><a name="l00913"></a><span class="lineno">  913</span>&#160;            (bcast_dim_left_index + params.bcast_dim_size) /</div>
<div class="line"><a name="l00914"></a><span class="lineno">  914</span>&#160;            input_bcast_dim_size * input_bcast_dim_size;</div>
<div class="line"><a name="l00915"></a><span class="lineno">  915</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">int</span> copy_bcast_dim =</div>
<div class="line"><a name="l00916"></a><span class="lineno">  916</span>&#160;            IsColMajor ? 2 * params.inner_dim_count</div>
<div class="line"><a name="l00917"></a><span class="lineno">  917</span>&#160;                       : 2 * NumDims - 2 * params.inner_dim_count - 1;</div>
<div class="line"><a name="l00918"></a><span class="lineno">  918</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">int</span> broadcast_bcast_dim =</div>
<div class="line"><a name="l00919"></a><span class="lineno">  919</span>&#160;            IsColMajor ? 2 * params.inner_dim_count + 1</div>
<div class="line"><a name="l00920"></a><span class="lineno">  920</span>&#160;                       : 2 * NumDims - 2 * params.inner_dim_count - 2;</div>
<div class="line"><a name="l00921"></a><span class="lineno">  921</span>&#160; </div>
<div class="line"><a name="l00922"></a><span class="lineno">  922</span>&#160;        <span class="keywordflow">if</span> (first_multiple &gt; bcast_dim_left_index) {</div>
<div class="line"><a name="l00923"></a><span class="lineno">  923</span>&#160;          <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> head_size = first_multiple - bcast_dim_left_index;</div>
<div class="line"><a name="l00924"></a><span class="lineno">  924</span>&#160;          params.input_block_sizes[params.bcast_dim] = head_size;</div>
<div class="line"><a name="l00925"></a><span class="lineno">  925</span>&#160;          params.bcast_block_sizes[copy_bcast_dim] = head_size;</div>
<div class="line"><a name="l00926"></a><span class="lineno">  926</span>&#160;          params.bcast_input_strides[copy_bcast_dim] =</div>
<div class="line"><a name="l00927"></a><span class="lineno">  927</span>&#160;              params.input_block_strides[params.bcast_dim];</div>
<div class="line"><a name="l00928"></a><span class="lineno">  928</span>&#160;          params.bcast_block_strides[copy_bcast_dim] =</div>
<div class="line"><a name="l00929"></a><span class="lineno">  929</span>&#160;              params.output_strides[params.bcast_dim];</div>
<div class="line"><a name="l00930"></a><span class="lineno">  930</span>&#160;          params.bcast_block_sizes[broadcast_bcast_dim] = 1;</div>
<div class="line"><a name="l00931"></a><span class="lineno">  931</span>&#160;          params.bcast_input_strides[broadcast_bcast_dim] = 0;</div>
<div class="line"><a name="l00932"></a><span class="lineno">  932</span>&#160;          params.bcast_block_strides[broadcast_bcast_dim] =</div>
<div class="line"><a name="l00933"></a><span class="lineno">  933</span>&#160;              params.output_strides[params.bcast_dim] *</div>
<div class="line"><a name="l00934"></a><span class="lineno">  934</span>&#160;              params.input_dims[params.bcast_dim];</div>
<div class="line"><a name="l00935"></a><span class="lineno">  935</span>&#160; </div>
<div class="line"><a name="l00936"></a><span class="lineno">  936</span>&#160;          num_output_coeffs += BroadcastBlock(</div>
<div class="line"><a name="l00937"></a><span class="lineno">  937</span>&#160;              params.input_block_sizes, params.input_block_strides,</div>
<div class="line"><a name="l00938"></a><span class="lineno">  938</span>&#160;              params.bcast_block_sizes, params.bcast_block_strides,</div>
<div class="line"><a name="l00939"></a><span class="lineno">  939</span>&#160;              params.bcast_input_strides, bcast_offset, 0, scratch,</div>
<div class="line"><a name="l00940"></a><span class="lineno">  940</span>&#160;              materialized_output, materialized_input, materialized_input_size);</div>
<div class="line"><a name="l00941"></a><span class="lineno">  941</span>&#160;        }</div>
<div class="line"><a name="l00942"></a><span class="lineno">  942</span>&#160;        <span class="keywordflow">if</span> (first_multiple &lt; last_multiple) {</div>
<div class="line"><a name="l00943"></a><span class="lineno">  943</span>&#160;          params.input_block_sizes[params.bcast_dim] = input_bcast_dim_size;</div>
<div class="line"><a name="l00944"></a><span class="lineno">  944</span>&#160;          params.bcast_block_sizes[copy_bcast_dim] = input_bcast_dim_size;</div>
<div class="line"><a name="l00945"></a><span class="lineno">  945</span>&#160;          params.bcast_input_strides[copy_bcast_dim] =</div>
<div class="line"><a name="l00946"></a><span class="lineno">  946</span>&#160;              params.input_block_strides[params.bcast_dim];</div>
<div class="line"><a name="l00947"></a><span class="lineno">  947</span>&#160;          params.bcast_block_strides[copy_bcast_dim] =</div>
<div class="line"><a name="l00948"></a><span class="lineno">  948</span>&#160;              params.output_strides[params.bcast_dim];</div>
<div class="line"><a name="l00949"></a><span class="lineno">  949</span>&#160;          params.bcast_block_sizes[broadcast_bcast_dim] =</div>
<div class="line"><a name="l00950"></a><span class="lineno">  950</span>&#160;              (last_multiple - first_multiple) / input_bcast_dim_size;</div>
<div class="line"><a name="l00951"></a><span class="lineno">  951</span>&#160;          params.bcast_input_strides[broadcast_bcast_dim] = 0;</div>
<div class="line"><a name="l00952"></a><span class="lineno">  952</span>&#160;          params.bcast_block_strides[broadcast_bcast_dim] =</div>
<div class="line"><a name="l00953"></a><span class="lineno">  953</span>&#160;              params.output_strides[params.bcast_dim] *</div>
<div class="line"><a name="l00954"></a><span class="lineno">  954</span>&#160;              params.input_dims[params.bcast_dim];</div>
<div class="line"><a name="l00955"></a><span class="lineno">  955</span>&#160;          <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> offset = (first_multiple - bcast_dim_left_index) *</div>
<div class="line"><a name="l00956"></a><span class="lineno">  956</span>&#160;                               m_outputStrides[params.bcast_dim];</div>
<div class="line"><a name="l00957"></a><span class="lineno">  957</span>&#160; </div>
<div class="line"><a name="l00958"></a><span class="lineno">  958</span>&#160;          num_output_coeffs += BroadcastBlock(</div>
<div class="line"><a name="l00959"></a><span class="lineno">  959</span>&#160;              params.input_block_sizes, params.input_block_strides,</div>
<div class="line"><a name="l00960"></a><span class="lineno">  960</span>&#160;              params.bcast_block_sizes, params.bcast_block_strides,</div>
<div class="line"><a name="l00961"></a><span class="lineno">  961</span>&#160;              params.bcast_input_strides, bcast_offset, offset, scratch,</div>
<div class="line"><a name="l00962"></a><span class="lineno">  962</span>&#160;              materialized_output, materialized_input, materialized_input_size);</div>
<div class="line"><a name="l00963"></a><span class="lineno">  963</span>&#160;        }</div>
<div class="line"><a name="l00964"></a><span class="lineno">  964</span>&#160;        <span class="keywordflow">if</span> (last_multiple &lt; bcast_dim_left_index + params.bcast_dim_size) {</div>
<div class="line"><a name="l00965"></a><span class="lineno">  965</span>&#160;          <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> tail_size =</div>
<div class="line"><a name="l00966"></a><span class="lineno">  966</span>&#160;              bcast_dim_left_index + params.bcast_dim_size - last_multiple;</div>
<div class="line"><a name="l00967"></a><span class="lineno">  967</span>&#160;          params.input_block_sizes[params.bcast_dim] = tail_size;</div>
<div class="line"><a name="l00968"></a><span class="lineno">  968</span>&#160;          params.bcast_block_sizes[copy_bcast_dim] = tail_size;</div>
<div class="line"><a name="l00969"></a><span class="lineno">  969</span>&#160;          params.bcast_input_strides[copy_bcast_dim] =</div>
<div class="line"><a name="l00970"></a><span class="lineno">  970</span>&#160;              params.input_block_strides[params.bcast_dim];</div>
<div class="line"><a name="l00971"></a><span class="lineno">  971</span>&#160;          params.bcast_block_strides[copy_bcast_dim] =</div>
<div class="line"><a name="l00972"></a><span class="lineno">  972</span>&#160;              params.output_strides[params.bcast_dim];</div>
<div class="line"><a name="l00973"></a><span class="lineno">  973</span>&#160;          params.bcast_block_sizes[broadcast_bcast_dim] = 1;</div>
<div class="line"><a name="l00974"></a><span class="lineno">  974</span>&#160;          params.bcast_input_strides[broadcast_bcast_dim] = 0;</div>
<div class="line"><a name="l00975"></a><span class="lineno">  975</span>&#160;          params.bcast_block_strides[broadcast_bcast_dim] =</div>
<div class="line"><a name="l00976"></a><span class="lineno">  976</span>&#160;              params.output_strides[params.bcast_dim] *</div>
<div class="line"><a name="l00977"></a><span class="lineno">  977</span>&#160;              params.input_dims[params.bcast_dim];</div>
<div class="line"><a name="l00978"></a><span class="lineno">  978</span>&#160;          <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> offset = (last_multiple - bcast_dim_left_index) *</div>
<div class="line"><a name="l00979"></a><span class="lineno">  979</span>&#160;                               m_outputStrides[params.bcast_dim];</div>
<div class="line"><a name="l00980"></a><span class="lineno">  980</span>&#160; </div>
<div class="line"><a name="l00981"></a><span class="lineno">  981</span>&#160;          num_output_coeffs += BroadcastBlock(</div>
<div class="line"><a name="l00982"></a><span class="lineno">  982</span>&#160;              params.input_block_sizes, params.input_block_strides,</div>
<div class="line"><a name="l00983"></a><span class="lineno">  983</span>&#160;              params.bcast_block_sizes, params.bcast_block_strides,</div>
<div class="line"><a name="l00984"></a><span class="lineno">  984</span>&#160;              params.bcast_input_strides, bcast_offset, offset, scratch,</div>
<div class="line"><a name="l00985"></a><span class="lineno">  985</span>&#160;              materialized_output, materialized_input, materialized_input_size);</div>
<div class="line"><a name="l00986"></a><span class="lineno">  986</span>&#160;        }</div>
<div class="line"><a name="l00987"></a><span class="lineno">  987</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00988"></a><span class="lineno">  988</span>&#160;        <span class="comment">// b and c do not exist.</span></div>
<div class="line"><a name="l00989"></a><span class="lineno">  989</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">int</span> copy_bcast_dim =</div>
<div class="line"><a name="l00990"></a><span class="lineno">  990</span>&#160;            IsColMajor ? 2 * params.inner_dim_count</div>
<div class="line"><a name="l00991"></a><span class="lineno">  991</span>&#160;                       : 2 * NumDims - 2 * params.inner_dim_count - 1;</div>
<div class="line"><a name="l00992"></a><span class="lineno">  992</span>&#160;        params.input_block_sizes[params.bcast_dim] = params.bcast_dim_size;</div>
<div class="line"><a name="l00993"></a><span class="lineno">  993</span>&#160;        params.bcast_block_sizes[copy_bcast_dim] = params.bcast_dim_size;</div>
<div class="line"><a name="l00994"></a><span class="lineno">  994</span>&#160;        params.bcast_input_strides[copy_bcast_dim] =</div>
<div class="line"><a name="l00995"></a><span class="lineno">  995</span>&#160;            params.input_block_strides[params.bcast_dim];</div>
<div class="line"><a name="l00996"></a><span class="lineno">  996</span>&#160;        params.bcast_block_strides[copy_bcast_dim] =</div>
<div class="line"><a name="l00997"></a><span class="lineno">  997</span>&#160;            params.output_strides[params.bcast_dim];</div>
<div class="line"><a name="l00998"></a><span class="lineno">  998</span>&#160; </div>
<div class="line"><a name="l00999"></a><span class="lineno">  999</span>&#160;        num_output_coeffs += BroadcastBlock(</div>
<div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>&#160;            params.input_block_sizes, params.input_block_strides,</div>
<div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>&#160;            params.bcast_block_sizes, params.bcast_block_strides,</div>
<div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>&#160;            params.bcast_input_strides, bcast_offset, 0, scratch,</div>
<div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>&#160;            materialized_output, materialized_input, materialized_input_size);</div>
<div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>&#160;      }</div>
<div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>&#160; </div>
<div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>&#160;      <span class="keywordflow">return</span> num_output_coeffs;</div>
<div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>&#160;    }</div>
<div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>&#160;  }</div>
<div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>&#160; </div>
<div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> BroadcastBlock(</div>
<div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>&#160;      <span class="keyword">const</span> Dimensions&amp; input_block_sizes,</div>
<div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>&#160;      <span class="keyword">const</span> Dimensions&amp; input_block_strides,</div>
<div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>&#160;      <span class="keyword">const</span> BroadcastDimensions&amp; bcast_block_sizes,</div>
<div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>&#160;      <span class="keyword">const</span> BroadcastDimensions&amp; bcast_block_strides,</div>
<div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>&#160;      <span class="keyword">const</span> BroadcastDimensions&amp; bcast_input_strides, Index bcast_offset,</div>
<div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>&#160;      Index offset, TensorBlockScratch&amp; scratch,</div>
<div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>&#160;      ScalarNoConst* materialized_output, ScalarNoConst** materialized_input,</div>
<div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>&#160;      <span class="keywordtype">size_t</span>* materialized_input_size)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>&#160;    <span class="comment">// ---------------------------------------------------------------------- //</span></div>
<div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>&#160;    <span class="comment">// Tensor block descriptor for reading block from the input.</span></div>
<div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> input_offset = bcast_offset + offset;</div>
<div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>&#160;    TensorBlockDesc input_desc(</div>
<div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>&#160;        IsColMajor ? indexColMajor(input_offset) : indexRowMajor(input_offset),</div>
<div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>&#160;        input_block_sizes);</div>
<div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>&#160; </div>
<div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>&#160;    ArgTensorBlock input_block = m_impl.block(input_desc, scratch);</div>
<div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>&#160; </div>
<div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>&#160;    <span class="comment">// ---------------------------------------------------------------------- //</span></div>
<div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>&#160;    <span class="comment">// Materialize input block into a temporary memory buffer only if it&#39;s not</span></div>
<div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>&#160;    <span class="comment">// already available in the arg block.</span></div>
<div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>&#160;    <span class="keyword">const</span> ScalarNoConst* input_buffer = NULL;</div>
<div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>&#160; </div>
<div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>&#160;    <span class="keywordflow">if</span> (input_block.data() != NULL) {</div>
<div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>&#160;      <span class="comment">// Input block already has raw data, there is no need to materialize it.</span></div>
<div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>&#160;      input_buffer = input_block.data();</div>
<div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>&#160; </div>
<div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>&#160;      <span class="comment">// Otherwise we have to do block assignment into a temporary buffer.</span></div>
<div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>&#160; </div>
<div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>&#160;      <span class="comment">// Maybe reuse previously allocated buffer, or allocate a new one with a</span></div>
<div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>&#160;      <span class="comment">// scratch allocator.</span></div>
<div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>&#160;      <span class="keyword">const</span> <span class="keywordtype">size_t</span> input_total_size = input_block_sizes.TotalSize();</div>
<div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>&#160;      <span class="keywordflow">if</span> (*materialized_input == NULL ||</div>
<div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>&#160;          *materialized_input_size &lt; input_total_size) {</div>
<div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>&#160;        *materialized_input_size = input_total_size;</div>
<div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>&#160;        <span class="keywordtype">void</span>* mem = scratch.allocate(*materialized_input_size * <span class="keyword">sizeof</span>(Scalar));</div>
<div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>&#160;        *materialized_input = <span class="keyword">static_cast&lt;</span>ScalarNoConst*<span class="keyword">&gt;</span>(mem);</div>
<div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>&#160;      }</div>
<div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>&#160; </div>
<div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>&#160;      <span class="keyword">typedef</span> internal::TensorBlockAssignment&lt;</div>
<div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>&#160;          ScalarNoConst, NumDims, <span class="keyword">typename</span> ArgTensorBlock::XprType, <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>&gt;</div>
<div class="line"><a name="l01052"></a><span class="lineno"> 1052</span>&#160;          TensorBlockAssignment;</div>
<div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>&#160; </div>
<div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>&#160;      TensorBlockAssignment::Run(</div>
<div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>&#160;          TensorBlockAssignment::target(input_block_sizes, input_block_strides,</div>
<div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>&#160;                                        *materialized_input),</div>
<div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>&#160;          input_block.expr());</div>
<div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>&#160; </div>
<div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>&#160;      input_buffer = *materialized_input;</div>
<div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>&#160;    }</div>
<div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>&#160; </div>
<div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>&#160;    <span class="comment">// ---------------------------------------------------------------------- //</span></div>
<div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>&#160;    <span class="comment">// Copy data from materialized input block to the materialized output, using</span></div>
<div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>&#160;    <span class="comment">// given broadcast strides (strides with zeroes).</span></div>
<div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>&#160;    <span class="keyword">typedef</span> internal::TensorBlockIO&lt;ScalarNoConst, Index, 2 * NumDims, Layout&gt;</div>
<div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>&#160;        TensorBlockIO;</div>
<div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>&#160; </div>
<div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>&#160;    <span class="keyword">typename</span> TensorBlockIO::Src src(bcast_input_strides, input_buffer);</div>
<div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>&#160;    <span class="keyword">typename</span> TensorBlockIO::Dst dst(bcast_block_sizes, bcast_block_strides,</div>
<div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>&#160;                                      materialized_output + offset);</div>
<div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>&#160; </div>
<div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>&#160;    <span class="keywordflow">return</span> TensorBlockIO::Copy(dst, src);</div>
<div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>&#160;  }</div>
<div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>&#160; </div>
<div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>&#160;<span class="keyword">protected</span>:</div>
<div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>&#160;  <span class="keyword">const</span> Device EIGEN_DEVICE_REF m_device;</div>
<div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>&#160;  <span class="keyword">const</span> std::remove_reference_t&lt;Broadcast&gt; m_broadcast;</div>
<div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>&#160;  Dimensions m_dimensions;</div>
<div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>&#160;  array&lt;Index, NumDims&gt; m_outputStrides;</div>
<div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>&#160;  array&lt;Index, NumDims&gt; m_inputStrides;</div>
<div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>&#160;  TensorEvaluator&lt;ArgType, Device&gt; m_impl;</div>
<div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>&#160;};</div>
<div class="line"><a name="l01083"></a><span class="lineno"> 1083</span>&#160; </div>
<div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>&#160; </div>
<div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>&#160;} <span class="comment">// end namespace Eigen</span></div>
<div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>&#160; </div>
<div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>&#160;<span class="preprocessor">#endif </span><span class="comment">// EIGEN_CXX11_TENSOR_TENSOR_BROADCASTING_H</span></div>
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